Method require_tensor_as_shape

src/framework/assets/tensor_source.cpp:477–499

    for (size_t i = 0; i < absmax.size(); ++i) {
        scales[i] = nested_quant_map[absmax[i]] *
            nested_absmax[static_cast<size_t>(static_cast<int64_t>(i) / state.nested_blocksize)] +
            state.nested_offset;
    }
    const auto packed_values = raw_u8_values(packed);
    if (static_cast<int64_t>(packed_values.size()) != (elements + 1) / 2) {
        throw std::runtime_error("BNB NF4 packed byte count mismatch: " + metadata.name);
    }
    const int64_t block_count = (elements + state.blocksize - 1) / state.blocksize;
    if (static_cast<int64_t>(scales.size()) != block_count) {
        throw std::runtime_error("BNB NF4 absmax block count mismatch: " + metadata.name);
    }
    std::vector<float> values(static_cast<size_t>(elements));
    int64_t out = 0;
    for (const uint8_t byte : packed_values) {
        values[static_cast<size_t>(out)] =
            quant_map[(byte >> 4U) & 0x0FU] * scales[static_cast<size_t>(out / state.blocksize)];
        ++out;
        if (out < elements) {
            values[static_cast<size_t>(out)] =
                quant_map[byte & 0x0FU] * scales[static_cast<size_t>(out / state.blocksize)];
            ++out;
        }
    }
    RawTensorData out_data;
    out_data.metadata = {metadata.name, dtype_for_ggml_type(output_type), state.shape};
    out_data.bytes = encode_f32_tensor_data(metadata.name, values, shape_from_dims(state.shape), output_type);